Journal of Big Data Analytic and Artificial Intelligence
Vol 6 No 1 (2023): JBIDAI Juni 2023

Perbandingan Metode Euclidean Probability dan Teorema Bayes untuk Diagnosa Penyakit Gigi

Natalia Cangera (Unknown)
Yusni Amaliah (Unknown)
Gusmana, Roman (Unknown)



Article Info

Publish Date
30 Jun 2023

Abstract

Dental disease is a disease that interferes with the normal function of the teeth. Dental disease has almost similar symptoms, so it requires an expert system of dental disease diagnosis for the proper treatment before the disease becomes more serious. The research employs Euclidean probability and Bayes' Theorem. Euclidean probability is a case approach for measuring probability based on causes, while Bayes' Theorem is a mathematical formula for determining conditional probability. Both of these methods determine the disease percentage based on the input symptoms. Their differences reflect in the calculation. Research shows that the Bayesian analysis is better than Euclidean probability, as evidenced by the similarity in the systems diagnostic with experts of 80% accuracy, while Euclidean probability is 40%.

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Journal Info

Abbrev

JBIDAI

Publisher

Subject

Computer Science & IT

Description

JBIDAI adalah jurnal nasional berbahasa Indonesia versi online yang dikelola oleh Prodi Sistem Informasi STMIK PPKIA Tarakanita Rahmawati. Jurnal ini memuat hasil-hasil penelitian dengan cakupan fokus penelitian meliputi : Artificial Intelligence, Big Data, Data Mining, Information Retrieval, ...